Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_49KHR_2015-12-17_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50HLH_2016-01-03_final.stac-item
2016-01-29 12:14:38	ga_s2am_ard_3-2-1_49JGL_2016-01-29_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_49KHS_2016-02-15_final
2016-03-06 12:03:43	ga_s2am_ard_3-2-1_49KHQ_2016-03-06_final.stac-item
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_49JGN_2016-03-09_final.stac-item
2016-10-12 12:04:37	ga_s2am_ard_3-2-1_49JGM_2016-10-12_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49KHS_2016-10-22_final
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHS_2016-11-11_final
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_49JGM_2016-12-01_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HMG_2016-12-15_final
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_49JGJ_2017-01-20_final.stac-item
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_49KHP_2017-02-12_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50HLH_2017-02-26_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_49JGK_2017-05-30_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49JFM_2017-11-09_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49JGL_2017-12-16_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50HMJ_2018-01-19_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49JGK_2018-02-14_final.stac-item
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_49KHR_2018-05-15_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49JGN_2018-08-06_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50HLK_2018-09-19_final.stac-item
2018-11-28 11:56:42	ga_s2am_ard_3-2-1_50HMJ_2018-11-28_final.stac-item
2019-01-03 12:13:49	ga_s2am_ard_3-2-1_49KHR_2019-01-03_final.stac-item
2019-01-23 12:14:23	ga_s2am_ard_3-2-1_49KGP_2019-01-23_final.stac-item
2019-02-02 12:15:07	ga_s2am_ard_3-2-1_49JGL_2019-02-02_final.stac-item
2019-02-12 12:14:56	ga_s2am_ard_3-2-1_49JFM_2019-02-12_final.stac-item
2019-03-14 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-03-14_final.stac-item
2019-04-03 12:13:59	ga_s2am_ard_3-2-1_49KGR_2019-04-03_final.stac-item
2019-05-03 12:14:45	ga_s2am_ard_3-2-1_49JGN_2019-05-03_final.stac-item
2019-05-30 12:05:32	ga_s2am_ard_3-2-1_49JGK_2019-05-30_final.stac-item
2019-06-12 12:14:30	ga_s2am_ard_3-2-1_49KGP_2019-06-12_final.stac-item
2019-07-12 12:15:15	ga_s2am_ard_3-2-1_49JGL_2019-07-12_final.stac-item
2019-08-31 12:14:42	ga_s2am_ard_3-2-1_49JGN_2019-08-31_final.stac-item
2019-11-10 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2019-11-10_final.stac-item
2019-11-23 11:56:52	ga_s2am_ard_3-2-1_50HMJ_2019-11-23_final.stac-item
2019-12-19 12:13:48	ga_s2am_ard_3-2-1_49KHR_2019-12-19_final.stac-item
2019-12-26 12:03:54	ga_s2am_ard_3-2-1_49KHR_2019-12-26_final.stac-item
2020-01-25 12:05:22	ga_s2am_ard_3-2-1_49JGK_2020-01-25_final.stac-item
2020-03-25 12:05:25	ga_s2am_ard_3-2-1_49JGK_2020-03-25_final.stac-item
2020-05-21 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-05-21_final.stac-item
2020-05-27 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-05-27_final.stac-item
2020-06-10 11:56:57	ga_s2am_ard_3-2-1_50HMJ_2020-06-10_final.stac-item
2020-06-17 11:47:16	ga_s2am_ard_3-2-1_50HMH_2020-06-17_final.stac-item
2020-07-03 12:04:04	ga_s2am_ard_3-2-1_49KHR_2020-07-03_final.stac-item
2020-07-10 11:56:44	ga_s2am_ard_3-2-1_50HLK_2020-07-10_final.stac-item
2020-08-05 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-08-05_final.stac-item
2020-10-01 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-10-01_final.stac-item
2020-10-24 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-10-24_final.stac-item
2020-10-28 11:56:45	ga_s2am_ard_3-2-1_50HLK_2020-10-28_final.stac-item
2021-02-21 12:13:54	ga_s2am_ard_3-2-1_49KHR_2021-02-21_final.stac-item
2021-02-28 12:04:46	ga_s2am_ard_3-2-1_49JGN_2021-02-28_final.stac-item
2021-03-30 12:03:42	ga_s2am_ard_3-2-1_49KHS_2021-03-30_final
2021-04-06 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2021-04-06_final.stac-item
2021-04-06 11:56:53	ga_s2am_ard_3-2-1_50HMH_2021-04-06_final.stac-item
2021-04-26 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-04-26_final.stac-item
2021-05-12 12:13:54	ga_s2am_ard_3-2-1_49KHR_2021-05-12_final.stac-item
2021-05-12 12:14:55	ga_s2am_ard_3-2-1_49JGM_2021-05-12_final.stac-item
2021-06-28 12:05:02	ga_s2am_ard_3-2-1_49JGM_2021-06-28_final.stac-item
2021-07-01 12:14:00	ga_s2am_ard_3-2-1_49KGR_2021-07-01_final.stac-item
2021-08-07 12:04:49	ga_s2am_ard_3-2-1_49JGN_2021-08-07_final.stac-item
2021-08-30 12:14:28	ga_s2am_ard_3-2-1_49KGP_2021-08-30_final.stac-item
2021-09-19 12:13:57	ga_s2am_ard_3-2-1_49KHR_2021-09-19_final.stac-item
2021-10-03 11:56:45	ga_s2am_ard_3-2-1_50HLK_2021-10-03_final.stac-item
2021-11-15 12:05:16	ga_s2am_ard_3-2-1_49JGL_2021-11-15_final.stac-item
2021-12-15 12:05:15	ga_s2am_ard_3-2-1_49JGL_2021-12-15_final.stac-item
2021-12-22 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-12-22_final.stac-item
2021-12-29 11:47:26	ga_s2am_ard_3-2-1_50HMG_2021-12-29_final
2022-01-14 12:05:16	ga_s2am_ard_3-2-1_49JGL_2022-01-14_final.stac-item
2022-02-06 12:13:54	ga_s2am_ard_3-2-1_49KHR_2022-02-06_final.stac-item
2022-02-17 11:47:15	ga_s2am_ard_3-2-1_50HLH_2022-02-17_final.stac-item
2022-03-28 12:14:29	ga_s2am_ard_3-2-1_49KGP_2022-03-28_final.stac-item
2022-04-24 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2022-04-24_final.stac-item
2022-04-27 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2022-04-27_final.stac-item
2022-05-04 12:05:11	ga_s2am_ard_3-2-1_49JGM_2022-05-04_final.stac-item
2022-06-13 12:05:11	ga_s2am_ard_3-2-1_49JGM_2022-06-13_final.stac-item
2022-08-05 12:15:07	ga_s2am_ard_3-2-1_49JGM_2022-08-05_final.stac-item
2022-08-22 12:05:13	ga_s2am_ard_3-2-1_49JGM_2022-08-22_final.stac-item
2022-11-20 12:05:16	ga_s2am_ard_3-2-1_49JGL_2022-11-20_final.stac-item
2022-12-23 12:14:39	ga_s2am_ard_3-2-1_49JGN_2022-12-23_final.stac-item
2023-01-09 12:05:13	ga_s2am_ard_3-2-1_49JGL_2023-01-09_final.stac-item
2023-01-19 12:03:54	ga_s2am_ard_3-2-1_49KHR_2023-01-19_final.stac-item
2023-01-22 12:13:54	ga_s2am_ard_3-2-1_49KGR_2023-01-22_final.stac-item
2023-02-08 12:04:59	ga_s2am_ard_3-2-1_49JGM_2023-02-08_final
2023-03-13 12:14:52	ga_s2am_ard_3-2-1_49JGM_2023-03-13_final
2023-04-09 12:05:15	ga_s2am_ard_3-2-1_49JGL_2023-04-09_final
2023-05-13 11:47:24	ga_s2am_ard_3-2-1_50HMG_2023-05-13_final
2023-06-01 12:13:58	ga_s2am_ard_3-2-1_49KHR_2023-06-01_final
2023-07-01 12:14:46	ga_s2am_ard_3-2-1_49JGN_2023-07-01_final
2023-07-01 12:15:15	ga_s2am_ard_3-2-1_49JGL_2023-07-01_final
2023-07-21 12:15:14	ga_s2am_ard_3-2-1_49JGL_2023-07-21_final
2023-07-28 12:05:20	ga_s2am_ard_3-2-1_49JGL_2023-07-28_final
2023-09-19 12:14:30	ga_s2am_ard_3-2-1_49KGP_2023-09-19_final
2023-11-05 12:05:00	ga_s2am_ard_3-2-1_49JGM_2023-11-05_final
2023-11-15 12:03:58	ga_s2am_ard_3-2-1_49KHR_2023-11-15_final
2023-12-18 12:13:51	ga_s2am_ard_3-2-1_49KHR_2023-12-18_final
2023-12-28 12:13:52	ga_s2am_ard_3-2-1_49KHR_2023-12-28_final
2024-01-11 11:57:04	ga_s2am_ard_3-2-1_50HLH_2024-01-11_final
2024-02-13 12:04:58	ga_s2am_ard_3-2-1_49JGM_2024-02-13_final
2024-03-01 11:57:20	ga_s2am_ard_3-2-1_50HMG_2024-03-01_final

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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